@article{ ISI:000376585700004,
Author = {Scott, Finlay and Jardim, Ernesto and Millar, Colin P. and Cervino,
   Santiago},
Title = {{An Applied Framework for Incorporating Multiple Sources of Uncertainty
   in Fisheries Stock Assessments}},
Journal = {{PLOS ONE}},
Year = {{2016}},
Volume = {{11}},
Number = {{5}},
Month = {{MAY 10}},
Abstract = {{Estimating fish stock status is very challenging given the many sources
   and high levels of uncertainty surrounding the biological processes
   (e.g. natural variability in the demographic rates), model selection
   (e.g. choosing growth or stock assessment models) and parameter
   estimation. Incorporating multiple sources of uncertainty in a stock
   assessment allows advice to better account for the risks associated with
   proposed management options, promoting decisions that are more robust to
   such uncertainty. However, a typical assessment only reports the model
   fit and variance of estimated parameters, thereby underreporting the
   overall uncertainty. Additionally, although multiple candidate models
   may be considered, only one is selected as the `best' result,
   effectively rejecting the plausible assumptions behind the other models.
   We present an applied framework to integrate multiple sources of
   uncertainty in the stock assessment process. The first step is the
   generation and conditioning of a suite of stock assessment models that
   contain different assumptions about the stock and the fishery. The
   second step is the estimation of parameters, including fitting of the
   stock assessment models. The final step integrates across all of the
   results to reconcile the multi-model outcome. The framework is flexible
   enough to be tailored to particular stocks and fisheries and can draw on
   information from multiple sources to implement a broad variety of
   assumptions, making it applicable to stocks with varying levels of data
   availability The Iberian hake stock in International Council for the
   Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to
   demonstrate the framework, starting from length-based stock and indices
   data. Process and model uncertainty are considered through the growth,
   natural mortality, fishing mortality, survey catchability and
   stock-recruitment relationship. Estimation uncertainty is included as
   part of the fitting process. Simple model averaging is used to integrate
   across the results and produce a single assessment that considers the
   multiple sources of uncertainty.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Scott, F (Reprint Author), European Commiss, Joint Res Ctr, Inst Protect \& Secur Citizen, Maritime Affairs Unit, Via Enrico Fermi 2749, I-21027 Ispra, VA, Italy.
   Scott, Finlay; Jardim, Ernesto; Millar, Colin P., European Commiss, Joint Res Ctr, Inst Protect \& Secur Citizen, Maritime Affairs Unit, Via Enrico Fermi 2749, I-21027 Ispra, VA, Italy.
   Millar, Colin P., Marine Scotland, Freshwater Lab, Faskally PH16 5LB, Pitlochry, Scotland.
   Cervino, Santiago, Ctr Oceanog Vigo, Inst Espanol Oceanog, Subida Radio Faro 50, Vigo 36390, Spain.}},
DOI = {{10.1371/journal.pone.0154922}},
Article-Number = {{e0154922}},
ISSN = {{1932-6203}},
Keywords-Plus = {{HAKE MERLUCCIUS-MERLUCCIUS; NATURAL MORTALITY; MANAGEMENT IMPLICATIONS;
   MODEL SELECTION; GROWTH; FISH; SIZE; INFORMATION; PROJECTIONS;
   ESTIMATORS}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{finlay.scott@jrc.ec.europa.eu}},
ORCID-Numbers = {{cervino, santiago/0000-0003-4146-0890}},
Number-of-Cited-References = {{50}},
Times-Cited = {{1}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{DM8BN}},
Unique-ID = {{ISI:000376585700004}},
OA = {{gold}},
DA = {{2017-08-17}},
}

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P.","Cervino, S."],"year":2016,"bibtype":"article","biburl":"http://flr-project.org/flr.bib","bibdata":{"bibtype":"article","type":"Article","author":[{"propositions":[],"lastnames":["Scott"],"firstnames":["Finlay"],"suffixes":[]},{"propositions":[],"lastnames":["Jardim"],"firstnames":["Ernesto"],"suffixes":[]},{"propositions":[],"lastnames":["Millar"],"firstnames":["Colin","P."],"suffixes":[]},{"propositions":[],"lastnames":["Cervino"],"firstnames":["Santiago"],"suffixes":[]}],"title":"An Applied Framework for Incorporating Multiple Sources of Uncertainty in Fisheries Stock Assessments","journal":"PLOS ONE","year":"2016","volume":"11","number":"5","month":"MAY 10","abstract":"Estimating fish stock status is very challenging given the many sources and high levels of uncertainty surrounding the biological processes (e.g. natural variability in the demographic rates), model selection (e.g. choosing growth or stock assessment models) and parameter estimation. Incorporating multiple sources of uncertainty in a stock assessment allows advice to better account for the risks associated with proposed management options, promoting decisions that are more robust to such uncertainty. However, a typical assessment only reports the model fit and variance of estimated parameters, thereby underreporting the overall uncertainty. Additionally, although multiple candidate models may be considered, only one is selected as the `best' result, effectively rejecting the plausible assumptions behind the other models. We present an applied framework to integrate multiple sources of uncertainty in the stock assessment process. The first step is the generation and conditioning of a suite of stock assessment models that contain different assumptions about the stock and the fishery. The second step is the estimation of parameters, including fitting of the stock assessment models. The final step integrates across all of the results to reconcile the multi-model outcome. The framework is flexible enough to be tailored to particular stocks and fisheries and can draw on information from multiple sources to implement a broad variety of assumptions, making it applicable to stocks with varying levels of data availability The Iberian hake stock in International Council for the Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to demonstrate the framework, starting from length-based stock and indices data. Process and model uncertainty are considered through the growth, natural mortality, fishing mortality, survey catchability and stock-recruitment relationship. Estimation uncertainty is included as part of the fitting process. Simple model averaging is used to integrate across the results and produce a single assessment that considers the multiple sources of uncertainty.","publisher":"PUBLIC LIBRARY SCIENCE","address":"1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA","language":"English","affiliation":"Scott, F (Reprint Author), European Commiss, Joint Res Ctr, Inst Protect & Secur Citizen, Maritime Affairs Unit, Via Enrico Fermi 2749, I-21027 Ispra, VA, Italy. Scott, Finlay; Jardim, Ernesto; Millar, Colin P., European Commiss, Joint Res Ctr, Inst Protect & Secur Citizen, Maritime Affairs Unit, Via Enrico Fermi 2749, I-21027 Ispra, VA, Italy. Millar, Colin P., Marine Scotland, Freshwater Lab, Faskally PH16 5LB, Pitlochry, Scotland. Cervino, Santiago, Ctr Oceanog Vigo, Inst Espanol Oceanog, Subida Radio Faro 50, Vigo 36390, Spain.","doi":"10.1371/journal.pone.0154922","article-number":"e0154922","issn":"1932-6203","keywords-plus":"HAKE MERLUCCIUS-MERLUCCIUS; NATURAL MORTALITY; MANAGEMENT IMPLICATIONS; MODEL SELECTION; GROWTH; FISH; SIZE; INFORMATION; PROJECTIONS; ESTIMATORS","research-areas":"Science & Technology - Other Topics","web-of-science-categories":"Multidisciplinary Sciences","author-email":"finlay.scott@jrc.ec.europa.eu","orcid-numbers":"cervino, santiago/0000-0003-4146-0890","number-of-cited-references":"50","times-cited":"1","usage-count-last-180-days":"1","usage-count-since-2013":"7","journal-iso":"PLoS One","doc-delivery-number":"DM8BN","unique-id":"ISI:000376585700004","oa":"gold","da":"2017-08-17","bibtex":"@article{ ISI:000376585700004,\nAuthor = {Scott, Finlay and Jardim, Ernesto and Millar, Colin P. and Cervino,\n Santiago},\nTitle = {{An Applied Framework for Incorporating Multiple Sources of Uncertainty\n in Fisheries Stock Assessments}},\nJournal = {{PLOS ONE}},\nYear = {{2016}},\nVolume = {{11}},\nNumber = {{5}},\nMonth = {{MAY 10}},\nAbstract = {{Estimating fish stock status is very challenging given the many sources\n and high levels of uncertainty surrounding the biological processes\n (e.g. natural variability in the demographic rates), model selection\n (e.g. choosing growth or stock assessment models) and parameter\n estimation. Incorporating multiple sources of uncertainty in a stock\n assessment allows advice to better account for the risks associated with\n proposed management options, promoting decisions that are more robust to\n such uncertainty. However, a typical assessment only reports the model\n fit and variance of estimated parameters, thereby underreporting the\n overall uncertainty. Additionally, although multiple candidate models\n may be considered, only one is selected as the `best' result,\n effectively rejecting the plausible assumptions behind the other models.\n We present an applied framework to integrate multiple sources of\n uncertainty in the stock assessment process. The first step is the\n generation and conditioning of a suite of stock assessment models that\n contain different assumptions about the stock and the fishery. The\n second step is the estimation of parameters, including fitting of the\n stock assessment models. The final step integrates across all of the\n results to reconcile the multi-model outcome. The framework is flexible\n enough to be tailored to particular stocks and fisheries and can draw on\n information from multiple sources to implement a broad variety of\n assumptions, making it applicable to stocks with varying levels of data\n availability The Iberian hake stock in International Council for the\n Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to\n demonstrate the framework, starting from length-based stock and indices\n data. Process and model uncertainty are considered through the growth,\n natural mortality, fishing mortality, survey catchability and\n stock-recruitment relationship. Estimation uncertainty is included as\n part of the fitting process. Simple model averaging is used to integrate\n across the results and produce a single assessment that considers the\n multiple sources of uncertainty.}},\nPublisher = {{PUBLIC LIBRARY SCIENCE}},\nAddress = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},\nType = {{Article}},\nLanguage = {{English}},\nAffiliation = {{Scott, F (Reprint Author), European Commiss, Joint Res Ctr, Inst Protect \\& Secur Citizen, Maritime Affairs Unit, Via Enrico Fermi 2749, I-21027 Ispra, VA, Italy.\n Scott, Finlay; Jardim, Ernesto; Millar, Colin P., European Commiss, Joint Res Ctr, Inst Protect \\& Secur Citizen, Maritime Affairs Unit, Via Enrico Fermi 2749, I-21027 Ispra, VA, Italy.\n Millar, Colin P., Marine Scotland, Freshwater Lab, Faskally PH16 5LB, Pitlochry, Scotland.\n Cervino, Santiago, Ctr Oceanog Vigo, Inst Espanol Oceanog, Subida Radio Faro 50, Vigo 36390, Spain.}},\nDOI = {{10.1371/journal.pone.0154922}},\nArticle-Number = {{e0154922}},\nISSN = {{1932-6203}},\nKeywords-Plus = {{HAKE MERLUCCIUS-MERLUCCIUS; NATURAL MORTALITY; MANAGEMENT IMPLICATIONS;\n MODEL SELECTION; GROWTH; FISH; SIZE; INFORMATION; PROJECTIONS;\n ESTIMATORS}},\nResearch-Areas = {{Science \\& Technology - Other Topics}},\nWeb-of-Science-Categories = {{Multidisciplinary Sciences}},\nAuthor-Email = {{finlay.scott@jrc.ec.europa.eu}},\nORCID-Numbers = {{cervino, santiago/0000-0003-4146-0890}},\nNumber-of-Cited-References = {{50}},\nTimes-Cited = {{1}},\nUsage-Count-Last-180-days = {{1}},\nUsage-Count-Since-2013 = {{7}},\nJournal-ISO = {{PLoS One}},\nDoc-Delivery-Number = {{DM8BN}},\nUnique-ID = {{ISI:000376585700004}},\nOA = {{gold}},\nDA = {{2017-08-17}},\n}\n\n","author_short":["Scott, F.","Jardim, E.","Millar, C. 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